In recent years, use of High Definition (HD) video technology has grown exponentially, and spread into many different areas. For example, many movies, television programming, and online video streams are now routinely presented in high definition. HD video technology is also increasingly being used in the area of surveillance and wireless communications. For instance, HD capable cameras can provide highly detailed video streams, and enable the effective monitoring of remote sites, such as industrial parks.
HD video for surveillance and wireless communication applications use significant amounts of bandwidth. Some remote sites, however, can at most, reliably deliver a bandwidth of 128 Kbps. Such bandwidth capacities can make delivering high quality video streams nearly impossible.
To help facilitate the use of HD video, many video compression schemes (e.g., MPEG-1/2, MPEG-4, and H.264) exist to reduce the size of raw high definition video.
In general, low bandwidth and high resolution contradict each other in the field of video coding and transmission. Object-based coding, in which only objects that move are coded and transmitted at a high frame or update rate, can be utilized to save bandwidth. However, it is difficult to identify if a potential or candidate object is a real object or noise in the background of the scene. Accordingly, there has been a need for a method and system to provide techniques for effectively identifying noise and coding video background.